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1.
This paper contributes to the literature underscoring the importance of climatic variance by developing a framework for incorporating the means and tails of the distributions of rainfall and temperature into empirical models of agricultural production. The methodology is applied to estimate the impact of climate change on the discrete choice decision to adopt irrigation since it is an important adaptation to climate change. We develop a discrete choice model for the decision to install irrigation capacity that captures the effects of both climate means and extremes. Climatic means and frequencies of climatic events in the upper tails of the temperature and precipitation distributions are used to estimate the parameters of a normal distribution for temperature and a Weibull distribution for precipitation. Using estimates from a probit model, we examine the independent effects of changing climatic mean and variance on the probability of adopting irrigation. Increasing the mean temperature, holding variance constant, shifts the entire distribution toward warmer temperatures—increasing the frequency of extreme temperatures. For precipitation, the specification captures the separate effects of mean rainfall, frequency of rainfall, and frequency of extreme events. The results show that the tails of the temperature and precipitation distributions, not the means, are the dominant climatic determinants in irrigation adoption. The results also show that water availability, soil characteristics, farm size and operator demographics are important determinants of irrigation.  相似文献   

2.
The year 2021 was recorded as the 6th warmest since 1880. In addition to large-scale warming, 2021 will be remembered for its unprecedented climate extremes. Here, a review of selected high-impact climate extremes in 2021, with a focus on China, along with an extension to extreme events in North America and Europe is presented. Nine extreme events that occurred in 2021 in China are highlighted, including a rapid transition from cold to warm extremes and sandstorms in spring, consecutive drought in South China and severe thunderstorms in eastern China in the first half of the year, extremely heavy rainfall over Henan Province and Hubei Province during summer, as well as heatwaves, persistent heavy rainfall, and a cold surge during fall. Potential links of extremes in China to four global-scale climate extremes and the underlying physical mechanisms are discussed here, providing insights to understand climate extremes from a global perspective. This serves as a reference for climate event attribution, process understanding, and high-resolution modeling of extreme events.  相似文献   

3.
It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.  相似文献   

4.
W. May 《Climate Dynamics》2004,22(2-3):183-204
In this study the simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for the present-day and the future climate is investigated. This is done on the basis of a global time-slice experiment (TSL) with the ECHAM4 atmospheric general circulation model (GCM) at a high horizontal resolution of T106. The first time-slice (period: 1970–1999) represents the present-day climate and the second (2060–2089) the future climate. Moreover, observational rainfall data from the Global Precipitation Climatology Project (GPCP, 1997–2002) and rainfall data from the ECMWF re-analysis (ERA, 1958–2001) are considered. ERA reveals serious deficiencies in its representation of the variability and extremes of daily rainfall during the Indian summer monsoon. These are mainly a severe overestimation of the frequency of wet days over the oceans and in the Himalayas, where also the rainfall intensity is overestimated. Further, ERA shows unrealistically heavy rainfall events over the tropical Indian Ocean. The ECHAM4 atmospheric GCM at a horizontal resolution of T106, on the other hand, simulates the variability and extremes of daily rainfall in good agreement with the observations. The only marked deficiencies are an underestimation of the rainfall intensity on the west coast of the Indian peninsula and in Bangladesh, an overestimation over the tropical Indian Ocean, due to an erroneous northwestward extension of the tropical convergence zone, and an overestimation of the frequency of wet days in Tibet. Further, heavy rainfall events are relatively strong in the centre of the Indian peninsula. For the future, TSL predicts large increases in the rainfall intensity over the tropical Indian Ocean as well as in northern Pakistan and northwest India, but decreases in southern Pakistan, in the centre of the Indian peninsula, and over the western part of the Bay of Bengal. The frequency of wet days is markedly increased over the tropical Indian Ocean and decreased over the northern part of the Arabian Sea and in Tibet. The intensity of heavy rainfall events is generally increased in the future, with large increases over the Arabian Sea and the tropical Indian Ocean, in northern Pakistan and northwest India as well as in northeast India, Bangladesh, and Myanmar.  相似文献   

5.
Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south–central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century over south–central Canada under a changing climate. The implications of these increases need be taken into consideration and integrated into policies and planning for adaptation strategies, including measures to incorporate climate change into engineering infrastructure design standards and disaster risk reduction measures. This paper briefly summarized these climate change research projects, focusing on the modeling methodologies and results, and attempted to use plain language to make the results more accessible and interesting to the broader informed audience. These research projects have been used to support decision-makers in south–central Canada when dealing with future extreme weather events under climate change.  相似文献   

6.
This study uses a long dataset of past debris flows from eight high-elevation catchments in the Swiss Alps for which triggering conditions since AD 1864 have been reconstructed. The torrents under investigation have unlimited sediment supply and the triggering of debris flows is thus mainly controlled by climatic factors. Based on point-based downscaled climate scenarios for meteorological stations located next to the catchments and for the periods 2001–2050 and 2051–2100, we study the evolution of temperature and rainfall above specific thresholds (10, 20, 30, 40 and 50 mm) and durations (1, 2 or 3 days). We conclude that the drier conditions in future summers and the wetting of springs, falls and early winters are likely to have significant impacts on the behavior of debris flows. Based on the current understanding of debris-flow systems and their reaction to rainfall inputs, one might expect only slight changes in the overall frequency of events by the mid-21st century, but possibly an increase in the overall magnitude of debris flows due to larger volumes of sediment delivered to the channels and an increase in extreme precipitation events. In the second half of the 21st century, the number of days with conditions favorable for the release of debris flows will likely decrease, especially in summer. The anticipated increase of rainfall during the shoulder seasons (March, April, November, December) is not expected to compensate for the decrease in future heavy summer rainfall over 2 or 3 days.  相似文献   

7.
Jinwon Kim 《Climatic change》2005,68(1-2):153-168
The effects of increased atmospheric CO2 on the frequency of extreme hydrologic events in the Western United States (WUS) for the 10-yr period of 2040–2049 are examined using dynamically downscaled regional climate change signals. For assessing the changes in the occurrence of hydrologic extremes, downscaled climate change signals in daily precipitation and runoff that are likely to indicate the occurrence of extreme events are examined. Downscaled climate change signals in the selected indicators suggest that the global warming induced by increased CO2 is likely to increase extreme hydrologic events in the WUS. The indicators for heavy precipitation events show largest increases in the mountainous regions of the northern California Coastal Range and the Sierra Nevada. Increased cold season precipitation and increased rainfall-portion of precipitation at the expense of snowfall in the projected warmer climate result in large increases in high runoff events in the Sierra Nevada river basins that are already prone to cold season flooding in todays climate. The projected changes in the hydrologic characteristics in the WUS are mainly associated with higher freezing levels in the warmer climate and increases in the cold season water vapor influx from the Pacific Ocean.  相似文献   

8.
The design of stormwater infrastructure is based on an underlying assumption that the probability distribution of precipitation extremes is statistically stationary. This assumption is called into question by climate change, resulting in uncertainty about the future performance of systems constructed under this paradigm. We therefore examined both historical precipitation records and simulations of future rainfall to evaluate past and prospective changes in the probability distributions of precipitation extremes across Washington State. Our historical analyses were based on hourly precipitation records for the time period 1949–2007 from weather stations in and near the state’s three major metropolitan areas: the Puget Sound region, Vancouver (WA), and Spokane. Changes in future precipitation were evaluated using two runs of the Weather Research and Forecast (WRF) regional climate model (RCM) for the time periods 1970–2000 and 2020–2050, dynamically downscaled from the ECHAM5 and CCSM3 global climate models. Bias-corrected and statistically downscaled hourly precipitation sequences were then used as input to the HSPF hydrologic model to simulate streamflow in two urban watersheds in central Puget Sound. Few statistically significant changes were observed in the historical records, with the possible exception of the Puget Sound region. Although RCM simulations generally predict increases in extreme rainfall magnitudes, the range of these projections is too large at present to provide a basis for engineering design, and can only be narrowed through consideration of a larger sample of simulated climate data. Nonetheless, the evidence suggests that drainage infrastructure designed using mid-20th century rainfall records may be subject to a future rainfall regime that differs from current design standards.  相似文献   

9.
According to the Anderson-Darling principle, a method for forecast of extremely heavy rainfall (abbreviated as extreme rainfall/precipitation) was developed based on the ensemble forecast data of the T213 global ensemble prediction system (EPS) of the China Meteorological Administration (CMA). Using the T213 forecast precipitation data during 2007-2010 and the observed rainfall data in June-August of 2001-2010, characteristics of the cumulative distribution functions (CDFs) of the observed and the T213 EPS forecast precipitation were analyzed. Accordingly, in the light of the continuous differences of the CDFs between model climate and EPS forecasts, a mathematical model of Extreme Precipitation Forecast Index (EPFI) was established and applied to forecast experiments of several extreme rainfall events in China during 17-31 July 2011. The results show that the EPFI has taken advantage of the tail information of the model climatic CDF and provided agreeable forecasts of extreme rainfalls. The EPFI based on the T213 EPS is useful for issuing early warnings of extreme rainfalls 3-7 days in advance. With extension of the forecast lead time, the EPFI becomes less skillful. The results also demonstrate that the rationality of the model climate CDF was of vital importance to the skill of EPFI.  相似文献   

10.
Global warming is expected to affect both the frequency and severity of extreme weather events, though projections of the response of these events to climate warming remain highly uncertain. The range of changes reported in the climate modelling literature is very large, sometimes leading to contradictory results for a given extreme weather event. Much of this uncertainty stems from the incomplete understanding of the physics of extreme weather processes, the lack of representation of mesoscale processes in coarse-resolution climate models, and the effect of natural climate variability at multi-decadal time scales. However, some of the spread in results originates simply from the variety of scenarios for future climate change used to drive climate model simulations, which hampers the ability to make generalizations about predicted changes in extreme weather events. In this study, we present a meta-analysis of the literature on projected future extreme weather events in order to quantify expected changes in weather extremes as a function of a common metric of global mean temperature increases. We find that many extreme weather events are likely to be significantly affected by global warming. In particular, our analysis indicates that the overall frequency of global tropical cyclones could decrease with global warming but that the intensity of these storms, as well as the frequency of the most intense cyclones could increase, particularly in the northwestern Pacific basin. We also found increases in the intensity of South Asian monsoonal rainfall, the frequency of global heavy precipitation events, the number of North American severe thunderstorm days, North American drought conditions, and European heatwaves, with rising global mean temperatures. In addition, the periodicity of the El Niño–Southern Oscillation may decrease, which could, in itself, influence extreme weather frequency in many areas of the climate system.  相似文献   

11.
A method for adjusting dynamically downscaled precipitation and temperature scenarios representing specific sites is presented. The method reproduces mean monthly values and standard deviations based on daily observations. The trend obtained in the regional climate model both for temperature and precipitation is maintained, and the frequency of modelled and observed rainy days shows better agreement. Thus, the method is appropriate for tailoring dynamically downscaled temperature and precipitation values for climate change impact studies. One precipitation and temperature scenario dynamically downscaled with HIRHAM from the Atmospheric-Ocean General Circulation Model at the Max-Planck Institute in Hamburg, ECHAM4/OPYC4 GSDIO with emission scenario IS92a, is chosen to illustrate the adjustment method.  相似文献   

12.
极端天气气候事件监测与预测研究进展及其应用综述   总被引：8，自引：2，他引：6  
极端天气气候事件(简称"极端事件")分为单站极端事件和区域性极端事件。本文回顾了极端事件的研究进展,首先回顾了单站极端温度、极端降水和干旱事件的观测研究及相关指数,进而对近年来不断增多的区域性极端事件研究做了简要回顾,最后还回顾了极端事件气候预测研究进展。同时,对国内外在极端事件气候监测和预测业务现状进行了初步总结,并指出:在极端事件气候监测方面中国的业务产品较丰富,并率先开展了针对区域性极端事件的监测业务,但在产品表现形式上缺乏统一组织,特别是英文产品表现力严重不足;在极端事件气候预测方面,国家气候中心发展了两种方法:一个是基于物理统计的BP-CCA和OSR的干旱预测方法,另一个基于国家气候中心月动力延伸预报模式(DERF)的高温预测方法。最后,对极端事件监测和预测业务发展及相关科学问题给出展望,指出应根据极端事件的业务需求继续加强相关研究和业务能力建设。  相似文献   

13.
The possible changes in the frequency of extreme rainfall events in Hong Kong in the 21st century wereinvestigated by statistically downscaling 30 sets of the daily global climate model projections (involvinga combination of 12 models and 3 greenhouse gas emission scenarios,namely,A2,A1B,and B1) of theFourth Assessment Report of the Intergovernmental Panel on Climate Change.To cater for the intermittentand skewed character of the daily rainfall,multiple stepwise logistic regression and multiple stepwise linearregression were employed to develop the downscaling models for predicting rainfall occurrence and rainfallamount,respectively.Verification of the simulation of the 1971-2000 climate reveals that the models ingeneral have an acceptable skill in reproducing past statistics of extreme rainfall events in Hong Kong.Theprojection results suggest that,in the 21st century,the annual number of rain days in Hong Kong is expectedto decrease while the daily rainfall intensity will increase,concurrent with the expected increase in annualrainfall.Based on the multi-model scenario ensemble mean,the annual number of rain day is expected todrop from 104 days in 1980-1999 to about 77 days in 2090-2099.For extreme rainfall events,about 90% ofthe model-scenario combinations indicate an increase in the annual number of days with daily rainfall 100mm (R100) towards the end of the 21st century.The mean number of R100 is expected to increase from 3.5days in 1980-1999 to about 5.3 days in 2090-2099.The projected changes in other extreme rainfall indicesalso suggest that the rainfall in Hong Kong in the 21st century may also become more extreme with moreuneven distributions of wet and dry periods.While most of the model-emission scenarios in general projectconsistent trends in the change of rainfall extremes in the 21st century,there is a large divergence in theprojections among different model/emission scenarios.This reflects that there are still large uncertainties inmodel simulations of future extreme rainfall events.  相似文献   

14.
吉林省单站暴雨特征分析及评估方法   总被引：5，自引：0，他引：5  
袭祝香  孙力  刘实 《气象科学》2009,29(2):230-234
利用吉林省50站1951-2007年逐日降水资料,对暴雨的时空分布规律和气候变化特征进行了分析,对单站暴雨采用等级、序位、异常气候重现期等方法进行了评估.结果表明:吉林省暴雨一般集中出现在7月上旬到8月下旬,且有一半以上的县市暴雨的气候倾向率呈上升的趋势,1980s中期以来,吉林省中东部地区暴雨出现次数处于偏多阶段.对吉林省单站暴雨采用等级、序位、异常气候重现期等方法进行了评估,对2005-2007年吉林省出现的大暴雨进行了试评估.  相似文献   

15.
This study explores the implications of recent extreme rainfall and flood events in the Sahel and the wider West African region for climate change adaptation. Are these events merely a temporal nuisance as suggested by the lingering desertification discourse or will more climatic extremes characterize the region over the next century? After reviewing incidences of severe rainfall and projected future climate variability, the paper examines local flood knowledge and decision-making, drawing upon a case study in Ghana. The data demonstrate that a variety of response strategies to flooding exist; yet, knowledge of and access to climate forecasts and other learning tools are essentially absent. So far, floods have not triggered mass displacement although cumulative environmental deterioration is likely to cause environmental refugees. The paper recommends to lay to rest the desertification narrative, consider the possibility of both floods and droughts, and mobilize local memory for anticipatory learning and practical adaptation.  相似文献   

16.
Regression-based statistical downscaling is a method broadly used to resolve the coarse spatial resolution of general circulation models. Nevertheless, the assessment of uncertainties linked with climatic variables is essential to climate impact studies. This study presents a procedure to characterize the uncertainty in regression-based statistical downscaling of daily precipitation and temperature over a highly vulnerable area (semiarid catchment) in the west of Iran, based on two downscaling models: a statistical downscaling model (SDSM) and an artificial neural network (ANN) model. Biases in mean, variance, and wet/dry spells are estimated for downscaled data using vigorous statistical tests for 30 years of observed and downscaled daily precipitation and temperature data taken from the National Center for Environmental Prediction reanalysis predictors for the years of 1961 to 1990. In the case of daily temperature, uncertainty is estimated by comparing monthly mean and variance of downscaled and observed daily data at a 95 % confidence level. In daily precipitation, downscaling uncertainties were evaluated from comparing monthly mean dry and wet spell lengths and their confidence intervals, cumulative frequency distributions of monthly mean of daily precipitation, and the distributions of monthly wet and dry days for observed and modeled daily precipitation. Results showed that uncertainty in downscaled precipitation is high, but simulation of daily temperature can reproduce extreme events accurately. Finally, this study shows that the SDSM is the most proficient model at reproducing various statistical characteristics of observed data at a 95 % confidence level, while the ANN model is the least capable in this respect. This study attempts to test uncertainties of regression-based statistical downscaling techniques in a semiarid area and therefore contributes to an improvement of the quality of predictions of climate change impact assessment in regions of this type.  相似文献   

17.
使用基于动力降尺度和统计降尺度方法得到的RCP4.5情景下的6.25 km高分辨率联合降尺度预估数据集,对长江经济带未来极端气候事件及其造成的风险展开评估和预估。结果表明：降尺度预估数据能较好的再现各极端温度指数和大部分极端降水指数的空间分布,但一些极端降水指数的偏差略大。未来长江经济带极端热事件将增加,冷事件减少;长江中游东部和下游的极端降水事件将增加,上游地区东南部发生干旱事件的可能性大。长江经济带以及上游、中游和下游3个分区的高温事件和强降水事件的国内生产总值（GDP）暴露度都将增加;人口暴露度呈先增后降的变化趋势。高温事件的GDP暴露度的分布因子和非线性因子的贡献同样重要,人口暴露度中分布因子的影响更大;强降水事件的暴露度主要取决于GDP或人口分布因子。  相似文献   

18.
Summary The present study is an analysis of the observed extreme temperature and precipitation trends over Yangtze from 1960 to 2002 on the basis of the daily data from 108 meteorological stations. The intention is to identify whether or not the frequency or intensity of extreme events has increased with climate warming over Yangtze River basin in the last 40 years. Both the Mann-Kendall (MK) trend test and simple linear regression were utilized to detect monotonic trends in annual and seasonal extremes. Trend tests reveal that the annual and seasonal mean maximum and minimum temperature trend is characterized by a positive trend and that the strongest trend is found in the winter mean minimum in the Yangtze. However, the observed significant trend on the upper Yangtze reaches is less than that found on the middle and lower Yangtze reaches and for the mean maximum is much less than that of the mean minimum. From the basin-wide point of view, significant increasing trends are observed in 1-day extreme temperature in summer and winter minimum, but there is no significant trend for 1-day maximum temperature. Moreover, the number of cold days ≤0 °C and ≤10 °C shows significant decrease, while the number of hot days (daily value ≥35 °C) shows only a minor decrease. The upward trends found in the winter minimum temperature in both the mean and the extreme value provide evidence of the warming-up of winter and of the weakening of temperature extremes in the Yangtze in last few decades. The monsoon climate implies that precipitation amount peaks in summer as does the occurrence of heavy rainfall events. While the trend test has revealed a significant trend in summer rainfall, no statistically significant change was observed in heavy rain intensity. The 1-day, 3-day and 7-day extremes show only a minor increase from a basin-wide point of view. However, a significant positive trend was found for the number of rainstorm days (daily rainfall ≥50 mm). The increase of rainstorm frequency, rather than intensity, on the middle and lower reaches contributes most to the positive trend in summer precipitation in the Yangtze.  相似文献   

19.
Observations as well as most climate model simulations are generally in accord with the hypothesis that the hydrologic cycle should intensify and become highly volatile with the greenhouse-gas-induced climate change, although uncertainties of these projections as well as the spatial and seasonal variability of the changes are much larger than for temperature extremes. In this study, we examine scenarios of changes in extreme precipitation events in 24 future climate runs of ten regional climate models, focusing on a specific area of the Czech Republic (central Europe) where complex orography and an interaction of other factors governing the occurrence of heavy precipitation events result in patterns that cannot be captured by global models. The peaks-over-threshold analysis with increasing threshold censoring is applied to estimate multi-year return levels of daily rainfall amounts. Uncertainties in scenarios of changes for the late 21st century related to the inter-model and within-ensemble variability and the use of the SRES-A2 and SRES-B2 greenhouse gas emission scenarios are evaluated. The results show that heavy precipitation events are likely to increase in severity in winter and (with less agreement among models) also in summer. The inter-model and intra-model variability and related uncertainties in the pattern and magnitude of the change is large, but the scenarios tend to agree with precipitation trends recently observed in the area, which may strengthen their credibility. In most scenario runs, the projected change in extreme precipitation in summer is of the opposite sign than a change in mean seasonal totals, the latter pointing towards generally drier conditions in summer. A combination of enhanced heavy precipitation amounts and reduced water infiltration capabilities of a dry soil may severely increase peak river discharges and flood-related risks in this region.  相似文献   

20.
Climate change has the potential ability to alter the occurrence and severity of extreme events. Though predicting changes of such extreme events is difficult, understanding them is important to determine the impacts of climate change in various sectors. This paper presents the change in rainfall extremes in the monsoon season in south-west Indian peninsula. Daily rainfall data were analysed for the entire Kerala state in India to determine if the extreme rainfall had changed over the 50-year period. Several indices were derived from the data to identify the extreme rainfalls. The trends of all the extreme indices were assessed by parametric ordinary least square regression technique, which were tested for significance at 95% level. Results showed significant decrease in monsoon rainfall extremes in Kerala that would affect the tendency of change in seasonal total rainfall. This study provides a comprehensive knowledge on extreme monsoon precipitation in Kerala, which could also be employed to study changing climate at local scale in other regions.  相似文献   

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